Monitoring sandy desertification of Otindag Sandy Land based on multi-date remote sensing images

Sandy desertification is now the main ecological problem in the Otindag Sandy Land. In order to reveal the process of land degradation, especially the latest situation of sandy desertification, a method integrating remote sensing, Geographic Information System (GIS) and field survey was employed to build a sandy desertification dataset for analysis. Remote sensing images included the Landsat Thematic Mapper (TM) image in 1987, the Enhanced Thematic Mapper Plus (ETM⁺) image in 2000, and the image with the Charge-Coupled Device Camera (CCD) on the China-Brazil Earth Resources Satellite (CBERS) in 2006. Five land-cover classes, including active sand dunes, fixed sand dunes, semi-fixed sand dunes, inter-dune grassland and wetlands, were identified. Results showed that the Otindag Sandy Land has been suffering sandy desertification since 1987 with 2 different desertified stages. The first stage from 1987 to 2000 was a severe sandy desertification period, characterized by the fixed sand dunes decreasing at a high speed, and the semi-fixed and active sand dunes increasing remarkably. The second stage spanned from 2000 to 2006 and the sandy desertification was weakened greatly. Although a large area of fixed sand dunes were transformed to other types, fixed sand dunes were still the dominant type in the Ointdag region at 2006. Spatial change detection based on active sand dunes showed that the expansion area was much larger than the reversion area in the past two decades, and that several active sand belts had been formed, suggesting that sandy desertification controlling of the Otindag Sandy Land will be a long-term task.     

Monitoring sandy desertification of Otindag Sandy Land based on multi-date remote sensing images

Sandy desertification is now the main ecological problem in the Otindag Sandy Land. In order to reveal the process of land degradation, especially the latest situation of sandy desertification, a method integrating remote sensing, Geographic Information System (GIS) and field survey was employed to build a sandy desertification dataset for analysis. Remote sensing images included the Landsat Thematic Mapper (TM) image in 1987, the Enhanced Thematic Mapper Plus (ETM⁺) image in 2000, and the image with the Charge-Coupled Device Camera (CCD) on the China-Brazil Earth Resources Satellite (CBERS) in 2006. Five land-cover classes, including active sand dunes, fixed sand dunes, semi-fixed sand dunes, inter-dune grassland and wetlands, were identified. Results showed that the Otindag Sandy Land has been suffering sandy desertification since 1987 with 2 different desertified stages. The first stage from 1987 to 2000 was a severe sandy desertification period, characterized by the fixed sand dunes decreasing at a high speed, and the semi-fixed and active sand dunes increasing remarkably. The second stage spanned from 2000 to 2006 and the sandy desertification was weakened greatly. Although a large area of fixed sand dunes were transformed to other types, fixed sand dunes were still the dominant type in the Ointdag region at 2006. Spatial change detection based on active sand dunes showed that the expansion area was much larger than the reversion area in the past two decades, and that several active sand belts had been formed, suggesting that sandy desertification controlling of the Otindag Sandy Land will be a long-term task.     

Impact of land use intensity on sandy desertification: An evidence from Horqin Sandy Land,China

It has been widely accepted that high land use intensity contributes to sandy desertification in Northern China. However, it is surprising that it is even not easy to find an explicit definition and proper indicator for the term “land use intensity” in the sandy desertification related literatures. To better understand the association between sandy desertification and its driving factors, especially in the context of the synergistic roles of both climatic and anthropogenic variables, an indicator for land use intensity was developed in this paper for quantifying the relative role of land use output on different kinds of vegetation cover. The results indicated land use intensity increased rapidly from 1980 to 1995, obviously decreased from 1995 to 2000, and increased slowly after 2000 as a result of the continued increase of socioeconomic pressures and the fluctuating changes in vegetative cover.An ARDL model was established and applied to analyze the correlation between the area of bare sand land and land use intensity with the influence of annual precipitation in temporal dimension. The area of bare sand land was significantly affected by land use intensity in the long run. However, in the short run, the area of bare sand land was mainly impacted by the auto-correlation effect of itself in temporal dimension and by the annual precipitation. The improvement of the sand dunes obviously reduced the risk of sandy desertification under the condition of specific land use intensity.Before analyzing the correlation between land use intensity and sandy desertification, specific skills were applied to improve the model, including data interpolation and regression verification, since there would be regression biases resulting from the acquisition and processing of time-series data of different sources. Results showed that the area of bare sand land (S_t)and the land use intensity (LI_t) were time-independent. Lag terms of these two variables were added to improve original model.Changes in socioeconomic pressures and ecological restoration projects had obvious influences on land use intensity. Along with the steady increase of socioecological pressures on land and the changes in vegetative cover resulting from various ecological protection strategies and ecological restoration projects, shifts in land use intensity followed a different trend with the population and the social-economic demands. Nonetheless, the continuous increase of socioeconomic demands will increase land use intensity in the long run, so that the risk of sandy desertification remains high.     

科尔沁沙地围封沙质草甸土壤种子库特征的研究

科尔沁沙地沙质草甸围封 5年后土壤种子库中植物种类有 38种 ,其中一、二年生草本植物 2 4种 ,多年生草本植物 9种 ,灌木 5种。土壤种子库密度为 (1385 5± 16 5 1)粒·m-2 ,其中 ,一、二年生草本植物所占的比例最大为 96 5 8% ,前 5种一、二年生草本植物黄蒿、灰绿藜、猪毛菜、狗尾草和画眉草占总数的 87 2 0 % ,而多年生草本植物和灌木类种子库密度分别占0 94 %和 2 4 8%。若以单子叶和双子叶植物统计 ,单子叶植物种子数占 13 13% ,双子叶植物的种子数占 86 87% ,其中豆科植物仅占 2 83%。土壤种子库中所有植物种的密度与其相对应的地面植物种的密度呈显著非完全相关性 ,其关系可用三次曲线来表示。从种子库组成分析 ,已围封 5年的沙质草甸植被仍处在黄蒿 -杂类草混合植被阶段。     

科尔沁沙地沙漠化土地恢复面临的挑战

对科尔沁沙地近50年来沙漠化土地面积、水资源可利用性、土地利用与草地植物生产力的变化进行了分析.结果发现：科尔沁沙地的土地沙漠化在经历了20世纪50—80年代中期的快速发展之后,80年代后期发生了逆转.在过去的50年中,西辽河径流量持续减小,1999年在西辽河中游的内蒙古自治区通辽市段断流;近20年来,位于科尔沁沙地腹地的西湖水位下降近10 m, 2001年干涸.科尔沁沙地草场的地上生物量由1937年的520 g·m^-2下降到2005年的197 g·m^-2.产生这种结果的主要原因是土地利用方式的变化,即基于灌溉的沙漠化治理规模的扩大和灌溉农田面积的增加,导致用水量增加.这也是科尔沁沙地实现土地沙漠化持续逆转面临的严峻挑战.     

放牧方式对浑善达克沙地榆树疏林退化的影响

浑善达克沙地榆树疏林是分布于草原地带的隐域植被类型,相较周边的典型草原区,其植被更加茂密,乔灌丛生,水草丰美,千百年来一直是牧民的优质冬季牧场。近半个世纪以来,因人类的过度开垦以及不合理的放牧管理,浑善达克沙地植被遭到空前的破坏,沙丘活化,载畜能力降低,生态价值和经济价值严重受损。近年来,随着国家草畜平衡以及禁牧政策的推广落实,放牧的牲畜总量得到一定程度的遏制,然而大面积草场还在继续退化。在牧民对生产生活的基本需求下,牲畜总量不可能无限制的压制。另外,适度的放牧对草原生态系统健康是有益的。因此,如何改良放牧方式,合理利用草场,在保持生态良好的基础上合理发挥草场的畜牧价值,是我们亟待探索的问题。以浑善达克沙地的典型天然植被榆树疏林为例,对不同放牧方式下的植被进行调查,基于沙地特殊的基质和植被特征,探讨适合沙地的放牧利用方式。研究表明,在相似的放牧强度下,把沙地作为冬营地,其榆树种群更新正常,植被覆盖度以及植物种类等均能保持良好,而把沙地作为夏季营地,榆树疏林植被退化严重,具体表现为:(1)榆树种群自然更新受阻;(2)灌木群落大量死亡或消失;(3)草本覆盖度显著降低,植物种类减少,多年生草...     

浑善达克沙地不同微地形的土壤物理性质和草本群落分布及其相关性分析

采用样方调查和室内检测相结合法对内蒙古浑善达克沙地迎风坡、坡顶、背风坡和丘间地不同土层(0~10、10~20和20~40 cm)的土壤物理性质(包括含水量、田间持水量、容重、总孔隙度和毛管孔隙度)及草本群落的生产力(包括盖度和地上部生物量)和物种多样性(包括Margalef丰富度指数、Simpson多样性指数、Shannon-Wiener多样性指数和Pielou均匀度指数)进行比较分析;在此基础上,采用Pearson相关性分析法对不同微地形的土壤物理性质与草本群落各指标间以及草本群落生产力与物种多样性各指标间的相关性进行分析.结果表明:4种微地形的土壤物理性质总体上差异显著,但不同土层的土壤物理性质总体上无明显差异;从丘间地、背风坡、坡顶到迎风坡,土壤的含水量、田间持水量、总孔隙度和毛管孔隙度依次递减,而土壤容重则依次递增,说明迎风坡的土壤结构较差且水分散失较多,而丘间地的土壤结构和水分状况均相对较好.不同微地形间草本群落生产力和物种多样性总体上也存在明显差异,从背风坡、丘间地、坡顶到迎风坡,草本群落的生产力和物种多样性依次递减,仅Margalef丰富度指数表现为在丘间地最高、在迎风坡最低,说明迎风坡的草本群落物种多样性较低,群落稳定性差,而背风坡和丘间地的草本群落物种多样性和生产力水平均较高,群落稳定性较好.相关性分析结果表明:该区域的草本群落生产力和物种多样性与土壤容重呈负相关,与土壤的其他物理性状呈正相关,但仅部分指标间有显著或极显著相关性;草本群落生产力与物种多样性各指标间呈正相关,但多数指标间的相关性并不显著.研究结果显示:微地形能够显著影响浑善达克沙地的土壤物理性质和草本群落的分布特征,气候和人为干扰使该沙地的土壤物理性质受到严重破坏,导致草本群落生产力降低并处于不稳定状态.     

Socio-ecological analysis of desertification in the Mu-Us Sandy Land with satellite remote sensing

To understand the contemporary process of desertification in the Mu-Us Sandy Land, China, we assessed the current status of desertification from satellite images. We analyzed the effect of land use by comparing desertification images and GIS-based thematic data. Socioeconomic factors were studied through interviews with local people. The desertified area ratio in each village was related to the sand dune ratio. Desertification in this region was affected by the activity of sand dunes. The revegetated area ratio had a close relationship with the cropland ratio. The development of cropland and surrounding woods contributed to revegetation of desertified land. Desertified areas were distributed mainly in pastoral regions. Critical carrying capacity of grassland for sheep and goats was approximately 2 head/ha. High population density of goats was evident in the severely desertified ranges. Goats were increasingly introduced to earn money through modernization, but they overgrazed fenced pastures. Further environmental education is needed to promote sustainable land use.     

浑善达克沙地中部典型固定沙丘植物群落分析

运用常规取样方法,2003年夏季对位于浑善达克沙地中部典型固定沙丘的植物群落进行了实地调查分析。结果表明,固定沙丘植物群落由阳坡、阴坡、沙脊、腰地、落沙坡、丘顶和风蚀坑植物群落组成,阴坡植物种类复杂,主要为耐阴乔木半乔木 灌木 柳灌丛类,群落较为稳定;阳坡主要以褐沙蒿、雾冰藜和虫实为主,种类组成较为简单,退化严重;沙脊为沙蒿 半旱生杂草类;腰地形成木岩黄芪 半灌木半旱生杂草类;落沙地形成虫实 狗尾草优势群落;风蚀坑形成狗尾草 虫实 褐沙蒿优势群落;顶部则形成虫实(63%)单优势群落。固定沙丘植物群落退化严重,需要加强保护,控制放牧强度,防止沙丘活化。     

时间信息熵及其在植被覆盖时空变化遥感检测中的应用

基于遥感影像的变化检测是当前的研究热点,可为区域生态环境保育、资源管理与发展规划等提供决策支撑。目前遥感影像的变化检测多基于两个时相,不能充分地反映植被在时间维的连续变化特征。通过引入信息论,提出了利用时间信息熵来综合表征植被长时间序列的变化特征。研究以延河流域为试验区,基于MODIS/NDVI数据,应用时间信息熵方法来计算了2000—2010年该区域的植被覆盖变化信息,厘清了时空变化特征。研究结果表明,近10年延河流域的植被覆盖的变化以增加为主,占流域面积的80.7%;植被覆盖明显增加的区域占流域面积13.9%,主要分布在流域的东北部和东南部;植被覆盖减少的区域占比2.4%,主要分布在流域的西部和西北部;严重减少的区域占比1.1%,主要分布在流域的中部和西南部,是需要重点的生态恢复与治理区域。时间信息熵方法与回归分析法相比,能够更为客观地表征长时间序列植被覆盖的连续变化强度和变化趋势,可为区域生态环境的保护和管理提供更为科学的理论依据。